No abstract

MS/MS experiments generate multiple, nearly identical spectra of the same peptide in various laboratories, but proteomics researchers typically do not leverage the unidentified spectra produced in other labs to decode spectra generated in their own labs. We propose a spectral archives approach that clusters MS/MS datasets, representing similar spectra by a single consensus spectrum. Spectral archives extend spectral libraries by analyzing both identified and unidentified spectra in the same way and maintaining information about spectra of peptides shared across species and conditions. Thus archives offer both traditional library spectrum similarity-based search capabilities along with novel ways to analyze the data. By developing a clustering tool, MS-Cluster, we generated a spectral archive from ~1.18 billion spectra that greatly exceeds the size of existing spectral repositories. We advocate that publicly available data should be organized into spectral archives, rather than be analyzed as disparate datasets, as is mostly the case today.

Supplementary data are available at Bioinformatics online.